Imitation of Demonstrations Using Bayesian Filtering With Nonparametric Data-Driven Models
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Material Type |
Article
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Author(s) |
Virani, Nurali (Author)
Jha, Devesh K. (Author)
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Source Journal Info. |
Title:
Journal of dynamic systems, measurement, and control
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Volume/ Issue No.: 2018/MAR V.140 N.3
Call No.:629.805 JDS Location: Periodicals & References Hall - 2nd floor
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Physical Description |
p 1-9
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Subject Area/ Descriptors |
Engineering
(39711)
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Abstract |
This paper addresses the problem of learning dynamic models of hybrid systems from demonstrations and then the problem of imitation of those demonstrations by using Bayesian filtering. A linear programming-based approach is used to develop nonparametric kernel-based conditional density estimation technique to infer accurate and concise dynamic models of system evolution from data. The training data for these models have been acquired from demonstrations by teleoperation....
Full Abstract
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Journal:
Journal of dynamic systems, measurement, and control
(1149)
Issu: 2018/MAR V.140 N.3
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